Medium- to Long-term Results of Strut Allografts Treating Periprosthetic Bone Defects
Bibliographic record
Abstract
PURPOSE: We evaluated the medium- to long-term outcomes of cortical strut allografts used to treat periprosthetic bone defects to better understand the correlation between radiological and clinical outcomes. MATERIALS AND METHODS: We retrospectively reviewed outcomes from 19 patients undergoing cortical strut allografts to treat periproshtetic bone defects from 2001 to 2015. The mean age at index operation was 59.4 years and the average follow-up period was 8.6 years. Surgeries were performed because of aseptic loosening (n=9), periprosthetic fractures (n=5), and infections (n=5). Each case was characterized and described in detail including the length of allograft and the union period; possible correlations between allograft length and detailed classification and union period was analyzed. Clinical evaluations included the Harris hip score and Kaplan-Meier survivorship. RESULTS: In revision total hip arthroplasty (THA), the average length of allografts used in patients experiencing fractures was significantly longer than those with aseptic loosening or infection. Of the 19 cases, incorporation was observed in 18 cases (94.7%). The average time to incorporation was 21.2 months and the time to incorporation was not significantly different among the two groups (fracture vs. aseptic loosening or infection). No positive correlation was identified between the length of allograft and incorporation period or in the time to cortical strut allograft incorporation among Paprosky or Vancouver subgroups. CONCLUSION: Results of cortical strut allografts show excellent incorporation rates based on medium- to long-term follow-up. Cortical strut allografts may be considered useful for the treatment of femoral bone defects experienced during revision THA and following periprosthetic fracture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".